AI
Engineering Production-ReadyAI Across Core Operations
Solve one high-impact enterprise AI challenge in 5 days. Governed. Measurable. Repeatable.
Get AI Running
AI Proves Itself in Pilots. Then Stalls.
You build a model. Accuracy hits 94% in testing. Leadership approves the budget. Then it sits. Deployment requires infrastructure you don't have. Model accuracy drops from 94% to 81% and nobody knows for months. Teams use LLMs without controls. Customer data gets sent to external AI tools. Personalization stays manual because the system to automate it never gets built. The model works. Getting it to run doesn't.
Wrong Problems Get Solved. High-Value Stays Unaddressed.
Cannot identify which AI use cases deliver measurable ROI. Pilots solve low-impact problems while expensive opportunities sit unaddressed.
Data too fragmented and ungoverned to feed models. AI initiatives stall because quality blocks deployment.
Performance Degrades Silently. Decisions Break.
Models deploy without monitoring. Accuracy drops from 94% to 81% as patterns shift and degradation goes undetected for months.
Decisions made on broken predictions. Problems discovered only after revenue drops or complaints surface.
Data Leaks Through LLMs. Compliance Can't Track.
Teams use ChatGPT, Claude, and Gemini without governance. Customer PII sent to external vendors with no audit trail.
Compliance can't track which models accessed what data or when. Regulatory and security risks unknown.
Scale Stays Manual. Automation Never Ships.
Deploy Models Now
Personalization is limited to five segments because AI doesn't reach production. Forecasts don't trigger actions. Churn signals don't activate retention workflows.
Revenue, inventory, and customers lost because automation stays theoretical.
AI Built to Last
High-impact use cases deploy. Performance monitoring catches degradation. Governance blocks data leaks. Personalization, forecasting, and churn prevention automate.
AI investment targets expensive problems
Use case selection based on business impact. Data structured before training. Teams deploy AI in weeks. Budget solves $5M problems, not concepts.
Accuracy holds under load
Performance tracking built into deployment. Degradation alerts trigger before impact. Models retrain automatically. Predictions maintain 90%+ accuracy for months.
Data stays inside your control
AI requests route through governance. Sensitive information stripped before leaving systems. Every query logged. Teams use AI safely. Violations prevented.
Revenue operations run on AI automation
Marketing delivers individualized content to 50,000 customers. Inventory orders place themselves. Retention offers reach customers 30 days before churn. Manual work replaced.
Enterprise AI Products for Secure, Governed Adoption
Enterprise-ready AI products that standardize access, enforce compliance, and keep AI usage aligned across the organization.
Secure AI interactions, enforce governance, and enable enterprise-wide AI adoption with confidence.
Protect every AI request with encrypted routing and policy guardrails so sensitive data never leaks. Apply role-based access, intelligent model routing, and full audit trails so teams can use AI safely while security and compliance stay intact.
Book a Demo →Deploy One AI Use Case. Replicate the Pattern.
Identify the problem worth solving. Build real-time infrastructure. Deploy with controls. Scale the pattern everywhere.
Start with a Bootcamp
Bootcamp
(5 Days)Prove one high-value AI use case
A 5-day engagement focused on one AI opportunity: personalization automation, demand forecasting, churn prevention, or another high-ROI problem.
Data readiness assessed. Use case validated against business impact. Feasibility confirmed using your actual data and systems. Pilot demonstrates a working AI solution.
Launchpad
(60 Days)Production with MLOps and governance
The AI model moves live with monitoring infrastructure. Performance tracking catches degradation. Retraining triggers automatically when accuracy drops.
AI governance layer activates. LLM usage routes through controls. Data leakage prevention enforces. Your teams operate the model daily.
Rollout
Extend pattern to additional use cases
The same MLOps and governance infrastructure supports new AI models. Each deployment takes less time because monitoring, governance, and data foundation already exist.
Personalization extends to new channels. Forecasting adds product categories. Churn prevention covers additional customer segments. Pattern replicates systematically.
Digital OS
All AI operations centralized
All AI models operate from single control layer. Performance monitors continuously. Governance enforces automatically. Retraining happens without manual intervention.
New models deploy in days using existing infrastructure. AI operations become self-service. Vendor dependencies eliminated.
Real-World AI Problems.Real Execution.
Practical behavioural intelligence execution across journeys, systems, and campaigns without replatforming.
View Case Study
Campaigns respond to live intent, not static segments
Real-time digital behavior fed into the campaign engine enabled journeys to react to actions, recover drop-offs, update segments, and adjust offers via interactions.
Turn AI Pilots into Production Systems
Monitoring for every model. Governance for every request. Automation for every workflow. Your systems running it
Built with Enterprise-Grade Partners
20 years building on Adobe, Salesforce, IBM, HCL, SAS, and Microsoft. We know how to make them work as one system.
Customer Endorsements
"The Xerago team demonstrated exceptional execution across analytics, AI-driven decisioning, and experience platforms. Their ability to orchestrate complex use cases across AEP, CJA, and Target on a single experience layer showed real maturity in applying AI and data to solve business problems."
— Head of Digital Experience & Intelligence
Enterprise Telecom Client
Perspectives on AI at Scale
Insights from deploying, monitoring, and governing AI across industries and use cases.
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